Paul G. Villarrubia

A practical methodology for early buffer and wire resource allocation

As technology scales, interconnect-centric design flows become imperative for achieving timing closure. Preplanning buffers and wires in the layout is critical for such flows. Both buffers and wires must be considered simultaneously, since wire routes determine buffer requirements and buffer locations constrain the wire routes. In contrast to recently proposed buffer-block planning approaches, our novel design methodology distributes a set of buffer sites throughout the design. This allows one to use a tile graph to abstract the buffer planning problem and simultaneously address wire planning. We present a four-stage heuristic called resource allocation for buffer and interconnect distribution for resource allocation that includes a new, efficient technique for buffer insertion using a length-based constraint. Extensive experiments validate the effectiveness of this approach.

The ISPD2005 placement contest and benchmark suite

Without the MCNC and ISPD98 benchmarks, it would arguably not have been possible for the academic community to make consistent advances in physical design over the last decade. While still being used extensively in placement and floorplanning research, those benchmarks can no longer be considered representative of todays (and tomorrows) physical design challenges. In order to drive physical design research over the next few years, a new benchmark suit is being released in conjunction with the ISPD2005 placement contest. These benchmarks are directly derived from industrial ASIC designs, with circuit sizes ranging from 210 thousand to 2.1 million placeable objects. Unlike the ISPD98 benchmarks, the physical structure of these designs is completely preserved, giving realistic challenging designs for todays placement tools. Hopefully, these benchmarks will help accelerate new physical design research in the placement, floor-planning, and routing.

Diffusion-based placement migration

Placement migration is the movement of cells within an existing placement to address a variety of post-placement design closure issues, such as timing, routing congestion, signal integrity, and heat distribution. To fix a design problem, one would like to perturb the design as little as possible while preserving the integrity of the original placement. This work presents a new diffusion-based placement method based on a discrete approximation to a closed-form solution of the continuous diffusion equation. It has the advantage of smooth spreading, which helps preserve neighborhood characteristics of the original placement. Applying this technique to placement legalization demonstrates significant improvements in wire length and timing compared to other commonly used techniques.

A semi-persistent clustering technique for VLSI circuit placement

Placement is a critical component of todays physical synthesis flow with tremendous impact on the final performance of VLSI designs. However, it accounts for a significant portion of the over-all physical synthesis runtime. With complexity and netlist size of todays VLSI design growing rapidly, clustering for placement can provide an attractive solution to manage affordable placement runtime. Such clustering, however, has to be carefully devised to avoid any adverse impact on the final placement solution quality. In this paper we present a new bottom-up clustering technique, called best-choice, targeted for large-scale placement problems. Our best-choice clustering technique operates directly on a circuit hypergraph and repeatedly clusters the globally best pair of objects. Clustering score manipulation using a priority-queue data structure enables us to identify the best pair of objects whenever clustering is performed. To improve the runtime of priority-queue-based best-choice clustering, we propose a lazy-update technique for faster updates of clustering score with almost no loss of solution quality. We also discuss a number of effective methods for clustering score calculation, balancing cluster sizes, and handling of fixed blocks. The effectiveness of our best-choice clustering methodology is demonstrated by extensive comparisons against other standard clustering techniques such as Edge-Coarsening [12] and First-Choice [13]. All clustering methods are implemented within an industrial placer CPLACE [1] and tested on several industrial benchmarks in a semi-persistent clustering context.

Transformational placement and synthesis

Novel methodology and algorithms to seamlessly integrate logic synthesis and physical placement through a transformational approach are presented. Contrary to most placement algorithms that minimize a global cost function based on an abstract representation of the design, we decomposed the placement function into a set of transforms and coupled them directly with incremental timing, noise, and/or power analyzers. This coupling results in a direct and more accurate feedback on optimizations for placement actions. These placement transforms are then integrated with traditional logic synthesis transforms leading to a converging set of optimizations based on the concurrent manipulation of boolean, electrical, as well as physical data. Experimental results indicate that the proposed approach creates an efficient converging design flow that eliminates placement and synthesis iteration. It results in timing improvements, and maintains other global placement measures such as wire congestion and wire length. The flexibility of the transformational approach allows us to easily add, extend and support more sophisticated algorithms that involve critical as well as non-critical regions and target a variety of metrics including noise, yield and manufacturability:.

Techniques for Fast Physical Synthesis

The traditional purpose of physical synthesis is to perform timing closure , i.e., to create a placed design that meets its timing specifications while also satisfying electrical, routability, and signal integrity constraints. In modern design flows, physical synthesis tools hardly ever achieve this goal in their first iteration. The design team must iterate by studying the output of the physical synthesis run, then potentially massage the input, e.g., by changing the floorplan, timing assertions, pin locations, logic structures, etc., in order to hopefully achieve a better solution for the next iteration. The complexity of physical synthesis means that systems can take days to run on designs with multimillions of placeable objects, which severely hurts design productivity. This paper discusses some newer techniques that have been deployed within IBMs physical synthesis tool called PDS that significantly improves throughput. In particular, we focus on some of the biggest contributors to runtime, placement, legalization, buffering, and electric correction, and present techniques that generate significant turnaround time improvements

RQL: global placement via relaxed quadratic spreading and linearization

This paper describes a simple and effective quadratic placement algorithm called RQL. We show that a good quadratic placement, followed by local wirelength-driven spreading can produce excellent results on large-scale industrial ASIC designs. As opposed to the current top performing academic placers [4,7,11], RQL does not embed a linearization technique within the solver. Instead, it only requires a simpler, pure quadratic objective function in the spirit of [8,10,23]. Experimental results show that RQL outperforms all available academic placers on the ISPD-2005 placement contest benchmarks. In particular, RQL obtains an average wire- length improvement of 2.8%, 3.2%, 5.4%, 8.5%, and 14.6% versus mPL6 [5], NTUPlaceS [7], Kraflwerk [20], APlace2.0 [11], and Capo10.2 [18], respectively. In addition, RQL is three, seven, and ten times faster than mpL6, Capo10.2, and APlace2.0, respectively. On the ISPD-2006 placement contest benchmarks, on average, RQL obtains the best scaled wirelength among all available academic placers.

Benchmarking for large-scale placement and beyond

Over the last five years, the large scale integrated circuit placement community achieved great strides in the understanding of placement problems, developed new high-performance algorithms, and achieved impressive empirical results. These advances have been supported by a nontrivial benchmarking infrastructure, and future achievements are set to draw on benchmarking as well. In this paper, we review motivations for benchmarking, especially for commercial electronic design automation, analyze available benchmarks, and point out major pitfalls in benchmarking. Our empirical data offers perhaps the first comprehensive evaluation of several leading large-scale placers on multiple benchmark families. We outline major outstanding problems and discuss the future of placement benchmarking. Furthermore, we attempt to extrapolate our experience to circuit layout tasks beyond placement.

Buffered Steiner trees for difficult instances

Buffer insertion has become an increasingly critical optimization in high performance design. The problem of finding a delay-optimal buffered Steiner tree has been an active area of research, and excellent solutions exist for most instances. However, current approaches fail to adequately solve a particular class of real-world “difficult” instances which are characterized by a large number of sinks, variations in sink criticalities, and varying polarity requirements. We propose a new Steiner tree construction called C-Tree for these instance types. When combined with van Ginneken style buffer insertion, C-Tree achieves higher quality solutions with fewer resources compared to traditional approaches.

The coming of age of physical synthesis

Physical synthesis, the integration of logic synthesis with physical design information, was born in the mid to late 1990s, which means it is about to enter its teenage years. Today, physical synthesis tools are a major part of the EDA industry, accounting for hundreds of millions of dollars in revenue. This work looks at how technology and design trends have affected physical synthesis over the last decade and also how physical synthesis will continue to evolve on its way to adulthood.